Keras Sequential Model Explained | Keras Sequential Model Example | Keras Tutorial | Simplilearn

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In this video, Keras Sequential Model Explained, we will talk in depth about sequential models in Keras. You will learn what Keras is and understand about computational graphs. You will get an idea about neural networks and how sequential model works. Finally, we'll see a Keras Sequential Model example with Python.

The below topics are covered in this Keras Sequential Model video:
1. What is Keras?
2. Computational Graphs
3. What are Neural Networks?
4. Sequential Models
5. Demo on Sequential models using Python.

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What is Keras?
Keras is a high-level, deep learning API developed by Google for implementing neural networks. It is written in Python and is used to make the implementation of neural networks easy. It also supports multiple backend neural network computation. Keras is relatively easy to learn and work with because it provides a python frontend with a high level of abstraction while having the option of multiple back-ends for computation purposes. This makes Keras slower than other deep learning frameworks, but extremely beginner-friendly.

What is Keras Sequential Model?
The core idea of Keras Sequential Model is to arrange the Keras layers in a sequential order. You can create a Sequential model by passing a list of layers to the Sequential constructor. To add a Keras layer, you can just create a layer using Keras API and then pass the layer through the add() function.

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